Urban Virtual Test Field for Highly Automated Vehicle Systems

  • Date: –17:00
  • Location: Online (see the ZOOM Link), but examination at room: 12167 (The Ångström Laboratory)
  • Lecturer: René Degen
  • Website
  • Organiser: Department of Electrical Engineering
  • Contact person: René Degen
  • Phone: +49 221-8275-4529
  • Licentiatseminarium

René Degen defends his licentiate thesis "Urban Virtual Test Field for Highly Automated Vehicle Systems"

Opponent: Dr. Bernhard Behr

Supervisors: Prof. Margot Ruschitzka and Prof. Mats Leijon.

Examiner: Professor Hans Bernhoff


Autonomous driving is one of the key technologies for increasing road safety and reducing traffic volumes. Therefore, science and industry are working together on new innovative solutions in this field of technology. One important component in this context is the approval and testing of new solution concepts with special focus on urban environments, because of the high diversity of traffic situations and the close contact between vulnerable road users (VRU) and automated vehicles.

In the course of this work, a novel approach for testing automated driving functions and vehicle systems in urban environments is presented. The goal is to create a safe and valid environment in which the automated vehicle and the VRU can meet and interact. The basis is a highly realistic virtual model of a city center. The physical behavior of the vehicle and VRU is recorded using measurement technology and transferred to the virtual city model. 

Based on representative urban traffic scenarios, the functionality of the urban test field is investigated from various points of view. Thereby, the focus lies on real-time capability and the quality of interaction between the vehicle and the VRU.

The investigations show that both, the real-time capability and the interaction possibilities, can be demonstrated. Further, the developed methodologies are suitable for real-time applications.

The seminar will be held online via Zoom: https://us04web.zoom.us/j/6114698997?pwd=K2lEQ2JmdnExaGFQbGVlaHhhbGkwQT09 (Meeting ID: 611 469 8997)